多智能體編隊中人工勢場法的改進(jìn)研究

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DOI：10.16652/j.issn.1004-373x.2025.17.027 引用格式：，.多智能體編隊中人工勢場法的改進(jìn)研究[J].現(xiàn)代電子技術(shù)，2025，48（17）：181-186.

關(guān)鍵詞：人工勢場法；多智能體編隊；局部最小值；衰減權(quán)重；斥力計算；權(quán)重分配中圖分類號：TN911.1-34；TP391.9 文獻(xiàn)標(biāo)識碼：A 文章編號：1004-373X（2025）17-0181-06

Application of improved artificial potential field method in multi-agent formation control

HEXing1，BAI Yanhong1，2

（1.SchoolofElectronicInformationEngineering，TaiuanUiversityofSienceandTechnology，TauanO3O24，Cina; ！CollegeoftellgentacuinustryaniUesityflctroicicdholoyinfea

Abstract：Sincethetraditionalartificialpotentialfieldmethodispronetofalingintolocalminima，animprovedartificial potentialfieldalgorithmwhichintroducesrepulsionattenuationweightisproposedaccording totheideaofdestroyingthe equilibriumstateofagentsatnon-targets.Thisalgorithmasignsweightstoobstaclesencounteredwithintheagent'sdetection rangeandapliestheseweightstothecalculationofrepulsiveforces exertedbytheobstacles.Theweightsdecayastheagent moves，ensuring thatthenetforceactingontheagentdoesnotbalanceoutbeforereaching thetarget，therebyalowing the agenttoescapelocalminia.Theresultsofthesimulationexperimentsdemonstratethat，incomparisonwiththetraditioalartificialpotentialfeldmethodandother methodsavoidinglocal minimasuchastherandomdisturbancemethodandtheedge-followingmethod，theproposedalgorithmavoidsthelocalminimaefectivelyandshowssignificantimprovementsinconvergence speed，stability and energy consumption.

Keywords：arificialpotentialfieldmethod;multi-agentformation;local minima;atenuationweight;repulsiveforcecalculation;weight allocation

0 引言

多智能體編隊在軍事、救援救災(zāi)、農(nóng)業(yè)生產(chǎn)、倉儲物流、交通管理等領(lǐng)域得到了廣泛應(yīng)用。（剩余6919字）